Struct ClusterConfig 

pub struct ClusterConfig {

    pub autoscaling_config: Option<AutoscalingConfig>,
    pub auxiliary_node_groups: Option<Vec<AuxiliaryNodeGroup>>,
    pub cluster_tier: Option<String>,
    pub cluster_type: Option<String>,
    pub config_bucket: Option<String>,
    pub dataproc_metric_config: Option<DataprocMetricConfig>,
    pub diagnostic_bucket: Option<String>,
    pub encryption_config: Option<EncryptionConfig>,
    pub endpoint_config: Option<EndpointConfig>,
    pub gce_cluster_config: Option<GceClusterConfig>,
    pub gke_cluster_config: Option<GkeClusterConfig>,
    pub initialization_actions: Option<Vec<NodeInitializationAction>>,
    pub lifecycle_config: Option<LifecycleConfig>,
    pub master_config: Option<InstanceGroupConfig>,
    pub metastore_config: Option<MetastoreConfig>,
    pub secondary_worker_config: Option<InstanceGroupConfig>,
    pub security_config: Option<SecurityConfig>,
    pub software_config: Option<SoftwareConfig>,
    pub temp_bucket: Option<String>,
    pub worker_config: Option<InstanceGroupConfig>,
}

The cluster config.

This type is not used in any activity, and only used as part of another schema.

Fields

autoscaling_config: Option<AutoscalingConfig>

Optional. Autoscaling config for the policy associated with the cluster. Cluster does not autoscale if this field is unset.

auxiliary_node_groups: Option<Vec<AuxiliaryNodeGroup>>

Optional. The node group settings.

cluster_tier: Option<String>

Optional. The cluster tier.

cluster_type: Option<String>

Optional. The type of the cluster.

config_bucket: Option<String>

Optional. A Cloud Storage bucket used to stage job dependencies, config files, and job driver console output. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location (US, ASIA, or EU) for your cluster’s staging bucket according to the Compute Engine zone where your cluster is deployed, and then create and manage this project-level, per-location bucket (see Dataproc staging and temp buckets (https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/staging-bucket)). This field requires a Cloud Storage bucket name, not a gs://… URI to a Cloud Storage bucket.

dataproc_metric_config: Option<DataprocMetricConfig>

Optional. The config for Dataproc metrics.

diagnostic_bucket: Option<String>

Optional. A Cloud Storage bucket used to collect checkpoint diagnostic data (https://cloud.google.com/dataproc/docs/support/diagnose-clusters#checkpoint_diagnostic_data). If you do not specify a diagnostic bucket, Cloud Dataproc will use the Dataproc temp bucket to collect the checkpoint diagnostic data. This field requires a Cloud Storage bucket name, not a gs://… URI to a Cloud Storage bucket.

encryption_config: Option<EncryptionConfig>

Optional. Encryption settings for the cluster.

endpoint_config: Option<EndpointConfig>

Optional. Port/endpoint configuration for this cluster

gce_cluster_config: Option<GceClusterConfig>

Optional. The shared Compute Engine config settings for all instances in a cluster.

gke_cluster_config: Option<GkeClusterConfig>

Optional. BETA. The Kubernetes Engine config for Dataproc clusters deployed to The Kubernetes Engine config for Dataproc clusters deployed to Kubernetes. These config settings are mutually exclusive with Compute Engine-based options, such as gce_cluster_config, master_config, worker_config, secondary_worker_config, and autoscaling_config.

initialization_actions: Option<Vec<NodeInitializationAction>>

Optional. Commands to execute on each node after config is completed. By default, executables are run on master and all worker nodes. You can test a node’s role metadata to run an executable on a master or worker node, as shown below using curl (you can also use wget): ROLE=$(curl -H Metadata-Flavor:Google http://metadata/computeMetadata/v1/instance/attributes/dataproc-role) if [[ “${ROLE}” == ‘Master’ ]]; then … master specific actions … else … worker specific actions … fi

lifecycle_config: Option<LifecycleConfig>

Optional. Lifecycle setting for the cluster.

master_config: Option<InstanceGroupConfig>

Optional. The Compute Engine config settings for the cluster’s master instance.

metastore_config: Option<MetastoreConfig>

Optional. Metastore configuration.

secondary_worker_config: Option<InstanceGroupConfig>

Optional. The Compute Engine config settings for a cluster’s secondary worker instances

security_config: Option<SecurityConfig>

Optional. Security settings for the cluster.

software_config: Option<SoftwareConfig>

Optional. The config settings for cluster software.

temp_bucket: Option<String>

Optional. A Cloud Storage bucket used to store ephemeral cluster and jobs data, such as Spark and MapReduce history files. If you do not specify a temp bucket, Dataproc will determine a Cloud Storage location (US, ASIA, or EU) for your cluster’s temp bucket according to the Compute Engine zone where your cluster is deployed, and then create and manage this project-level, per-location bucket. The default bucket has a TTL of 90 days, but you can use any TTL (or none) if you specify a bucket (see Dataproc staging and temp buckets (https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/staging-bucket)). This field requires a Cloud Storage bucket name, not a gs://… URI to a Cloud Storage bucket.

worker_config: Option<InstanceGroupConfig>

Optional. The Compute Engine config settings for the cluster’s worker instances.

Trait Implementations

impl Clone for ClusterConfig

fn clone(&self) -> ClusterConfig

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for ClusterConfig

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for ClusterConfig

fn default() -> ClusterConfig

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for ClusterConfig

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for ClusterConfig

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl Part for ClusterConfig